1. Technical Field
The present invention relates to video processing and more particularly to systems and methods for dealing with a large video corpus to analyze, track, classify and visualize videos or portions thereof.
2. Description of the Related Art
Video data differs from purely textual data in several important ways. Video is often easier to generate, but it is harder to manipulate, compare, and query over. Consequently, social repositories of video data such as YouTube™ depend on verbal title, tags, and descriptions for searching, even though each of these textual records can bear little relation to the actual video content. Sometimes this inaccuracy is deliberate for spamming purposes, but often it is due to the honest polysemy of words.
It is difficult to find a precision answer to a query with video. Retrieval of video content may be complicated by a server's heuristic attempts at query expansion, such as including videos whose supposed relevance to the query comes mainly from their popularity, or from their collocation within ill-formed playlists where other videos are in fact legitimate responses.
There are very many videos that are digitally accessible, but current search engines do not “look” at the videos, they simply describe the videos in words. Finding videos that are related to each other is difficult, and little progress has been made in this area, especially on large depositories like YouTube™.